Literature DB >> 20978508

A 50% higher prevalence of life-shortening chronic conditions among cancer patients with low socioeconomic status.

W J Louwman1, M J Aarts, S Houterman, F J van Lenthe, J W W Coebergh, M L G Janssen-Heijnen.   

Abstract

BACKGROUND: Comorbidity and socioeconomic status (SES) may be related among cancer patients.
METHOD: Population-based cancer registry study among 72,153 patients diagnosed during 1997-2006.
RESULTS: Low SES patients had 50% higher risk of serious comorbidity than those with high SES. Prevalence was increased for each cancer site. Low SES cancer patients had significantly higher risk of also having cardiovascular disease, chronic obstructive pulmonary diseases, diabetes mellitus, cerebrovascular disease, tuberculosis, dementia, and gastrointestinal disease. One-year survival was significantly worse in lowest vs highest SES, partly explained by comorbidity.
CONCLUSION: This illustrates the enormous heterogeneity of cancer patients and stresses the need for optimal treatment of cancer patients with a variety of concomitant chronic conditions.

Entities:  

Mesh:

Year:  2010        PMID: 20978508      PMCID: PMC2994221          DOI: 10.1038/sj.bjc.6605949

Source DB:  PubMed          Journal:  Br J Cancer        ISSN: 0007-0920            Impact factor:   7.640


People of a lower socioeconomic status (SES) generally have poorer health status and higher mortality than people of higher SES (Jemal ; Mackenbach ), also with respect to cancer, with in general higher incidence rate of all cancers combined among people from lower socioeconomic groups (Dalton ). A differential distribution of known risk factors for specific neoplasms between SES groups seems a likely explanation for the above inequalities. For example, the prevalence of smokers has become higher among lower classes (Lahelma ; Stronks ), probably resulting in higher rates of cancer of the lung, larynx, mouth, pharynx, oesophagus, and bladder (Siemiatycki ; Stellman and Resnicow, 1997; Tyczynski ). However, smoking is not only related to cancer but also to chronic obstructive pulmonary diseases (COPD) and cardiovascular diseases (Doll ). Hence, the high prevalence of comorbidity among lung cancer patients (Janssen-Heijnen ). Socioeconomic status may thus be associated with comorbidity among cancer patients. Thus, medical doctors are presented with a heterogeneous group of cancer patients, for whom appropriate individual treatment must be chosen, taking concomitant conditions into account (Ayanian ; Lash ; Janssen-Heijnen ; Lemmens ; Louwman ; van Spronsen ). We studied in a large population-based group of cancer patients the prevalence of comorbidity according to SES, not only by number of concomitant diseases, but also for specific diseases that affect patients with the various tumour sites.

Materials and methods

The Eindhoven Cancer Registry records data on all patients newly diagnosed with cancer in the south of the Netherlands (2.4 million inhabitants, 15% of the Dutch population); it also records serious comorbidity according to an adaptated list (Charlson ). Chronic obstructive pulmonary diseases, cardio- and cerebrovascular diseases, peripheral arterial disease, other malignancies, and diabetes mellitus, connective tissue diseases, rheumatoid arthritis, kidney, bowel, and liver diseases, dementia, tuberculosis and other chronic infections were also recorded. For most analyses peripheral arterial disease was included in the cardiovascular diseases, although gastrointestinal diseases were grouped (gastric diseases, Crohn's disease, ulcerative colitis, liver cirrhosis, and hepatitis). Comorbidity was defined as life-shortening disease that was present at the time of cancer diagnosis and/or received treatment or surveillance. Trained registry personnel actively collect data on diagnosis, staging, and treatment from the medical records after notification by pathologists and medical registration offices. Previous admissions, letters from and to general practitioners and other specialists, the medical history and preoperative screening were used as sources. Patients with cancer of the oesophagus, stomach, colon or rectum, pancreas, lung, melanoma, breast, cervix uteri, corpus uteri, ovary, prostate, bladder, kidney, and non-Hodgkin's lymphoma (NHL), newly diagnosed between 1997 and 2006 (n=72 153), were included in this study; cancers diagnosed at autopsy (n=369) were excluded. Statistics Netherlands developed an indicator of SES, using individual fiscal data on the economic value of the home and household income, and is provided at aggregated level for each postal code (covering an average of 17 households). Socioeconomic status was categorised as low (deciles 1–3), medium (deciles 4–7), or high social class (deciles 8–10), and a separate class for postal codes for a long-term care providing institution (such as a nursing home; van Duijn and Keij, 2002). We calculated the distribution of cancer patients across socioeconomic strata according to tumour localisation, also by gender and age. Patients for whom the SES was unknown (n=766, 1%) or for whom the postal code included a care providing institution (n=3569, 5%), as well as those with unknown comorbidity (n=8399, 12%) were excluded from the analyses of SES and comorbidity. Differences in distribution were tested with the χ test. Logistic regression analyses of the odds of having a specific concomitant disease were performed age- and gender-adjusted for all tumour sites combined, and according to tumour site for four concomitant diseases separately; cardiovascular disease, COPD, diabetes mellitus, and gastrointestinal disease. Statistical significance of an overall effect of SES on the prevalence of a specific condition was tested using the χ2-likelihood ratio test. Crude 1-year survival rates were calculated for all studied tumours combined and for the most important tumour sites separately. Cox's regression models were used to compute multivariate rates (hazard ratio=HR) and 95% confidence intervals (95% CI). The relative contribution (%) of adding comorbidity to the model was calculated as follows: ((HR model A−HR model B)/(HR model A−1)) × 100, where A is the basic model (age- and gender-adjusted) and in model B comorbidity is added to model A. All statistical analyses were performed using SAS V9.12 (SAS Institute Inc., Cary, NC, USA).

Results

Male cancer patients were older than female patients (Table 1), the median age being 69 and 64 years, respectively (P<0.0001). At the time of the diagnosis of the cancer 71% of male and 58% of female cancer patients had at least one concomitant disease. The most frequent concomitant condition for males with cancer was cardiovascular disease (23%), for women hypertension (20%), among cancer patients older than 70 the prevalence of these diseases was 34% and 31%, respectively. In the subgroup of cancer patients with two or more concomitant diseases, the most frequent combination of diseases among males was cardiovascular disease with hypertension (14%) and in females diabetes with hypertension (21%).
Table 1

Description of all cancer patients diagnosed with selected tumours between 1997 and 2006 in the Eindhoven Cancer Registry

  Males
Females
Total
  n % n % n %
Tumour localisation
 Oesophagus10793398114772
 Stomach172351032327554
 Colorectal68151960141712 82918
 Pancreas9072849217562
 Lung93542635911012 94518
 Melanoma140541899533045
 Breast 14 8594114 85920
 Cervix uteri 72527251
 Corpus uteri 2128621283
 Ovary 1540415402
 Prostate998727 998714
 Kidney12013806220073
 Urinary bladder23066679229854
 Non-Hodgkin's lymphoma184651413432594
       
Age
 <451156338841150407
 45–5966241810 5782917 20224
 60–7418 9845213 1423732 12644
 >7598592783292318 18825
       
SES
 Low95182699532819 47127
 Intermediate14 3093913 8243828 13339
 High10 8123097412720 55328
 Institution156942032636015
 Unknown415138317981
       
Comorbidity
Number of concomitant diseases
  010 6882914 8264125 51435
  110 7752993532620 12828
  >210 9923070502018 04225
  Unknown416811470413887212
       
Concomitant diseasea
  Previous cancer446012356510797711
  Cardiovascular disease8353233854111212717
  Peripheral arterial disease344591358447677
  COPD53471526747799411
  Hypertension63671771842013 46219
  Diabetes mellitus358610348210702610
  Cerebrovascular disease175451044327794
  Tuberculosis553240919471
  Central nervous systemb221135415681
  Gastrointestinal disease262971294439005
  Other diseases92531078319873
Total36 6235035 9335072 556100

Abbreviations: COPD=chronic obstructive pulmonary diseases; SES=socioeconomic status.

Patients may suffer from more than one condition.

Dementia in 96% of these patients.

The proportion of patients by SES varied for the different tumour sites (Table 2). Patients under age 70 with stomach, lung, bladder, or cervical cancer more often had low SES. High SES was more frequent among patients with melanoma or breast, colorectal, or prostate cancer in this age group.
Table 2

Distribution of cancer patients newly diagnosed in 1997–2006 according to gender, age and socioeconomic status (SES)

  Males
Females
  <70
70+
<70
70+
Tumour localisation No. of patients % low SES No. of patients % low SES No. of patients % low SES No. of patients % low SES
Oesophagus58923342371703016143
Stomach76726719373863146544
Colorectal317621266232226624263040
Pancreas43324339363252837444
Lung44982938273822263592350
Melanoma56315169337291619443
Breast907021309442
Cervix uteri4763712043
Corpus uteri11892557642
Ovary8752343842
Prostate393020414930
Kidney63922392323723130041
Urinary bladder855251027332163230840
Non-Hodgkin's lymphoma106021575317032551442
Total of these sites16 5102314 2013419 0032410 09742
Among patients aged 70+ with cancer of the oesophagus, stomach, or lung, low SES was clearly over-represented. High SES was more frequent among patients with prostate cancer or NHL. For all tumour localisations the proportion of patients without comorbidity was highest in the high SES group (Figure 1). A gradient towards more concomitant conditions appeared in lower SES groups (P<0.001), which had a significantly higher risk of cardiovascular disease (ORlow =1.4, 95% CI: 1.3–1.5), COPD (OR=1.8 (1.7–1.9)), diabetes mellitus (OR=1.5 (1.4–1.6)), cerebrovascular disease (OR=1.5 (1.4–1.7)), tuberculosis (OR=1.3 (1.1–1.6)), dementia (OR=1.3 (1.0–1.8)), gastrointestinal disease (OR=1.5 (1.4–1.6)), and two or more concomitant conditions (OR=1.8 (1.7–1.9)) in addition to their cancer (Table 3). The risk of having cancer and also at least one other serious concomitant disease was 50% higher in the low SES than in the high SES group (OR=1.5 (1.4–1.6)).
Figure 1

Number of concomitant diseases among cancer patients diagnosed in 1997–2006 in the Southeastern Netherlands. *Distribution of number of concomitant diseases significantly different from the highest socioeconomic status category.

Table 3

Risk of specific concomitant diseases according to SES adjusted for age and gender among cancer patients diagnosed in 1997–2006

  SES
Concomitant disease Low Intermediate High P a
Previous cancer1.010.991.000.7
Cardiovascular disease1.42b1.23b1.000.0001
COPD1.81b1.37b1.000.0001
Hypertension0.981.031.000.2
Diabetes mellitus1.52b1.32b1.000.0001
Cerebrovascular disease1.53b1.27b1.000.0001
Tuberculosis1.34b1.171.000.01
Central nervous system1.34b1.051.000.05
Gastrointestinal1.48b1.27b1.000.0001
Other1.22b1.101.000.01
1 or more concomitant disease1.50b1.24b1.000.0001
2 or more concomitant diseases1.80b1.36b1.000.0001

Abbreviations: COPD=chronic obstructive pulmonary diseases; SES=socioeconomic status.

P for overall effect of SES (χ2-likelihood ratio).

Confidence interval does not include 1.00.

For four concomitant conditions we stratified by tumour localisation (Figure 2). The risk of cardiovascular disease among low compared with high SES patients was significantly higher (1.4–1.6 times) for patients with stomach, colorectal, lung, breast, prostate, and bladder cancer. The risk of COPD was elevated among low SES patients with cancer of the stomach, colorectum, pancreas, lung, breast, corpus uteri, prostate, and kidney (OR's ranging from 1.4 to 2.2). The risk of diabetes mellitus was highest among people from low SES with breast cancer (OR=2.0 (1.2–2.4)) and the risk of gastrointestinal diseases was highest among patients with oesophageal cancer (OR=2.0 (1.2–3.4)).
Figure 2

Risk of four concomitant diseases among cancer patients with the lowest socioeconomic status (SES) compared with those with the highest SES (=reference, 1.00) according to tumour localisation with adjustment for age and gender. *95% confidence interval does not include 1.00; # No reliable estimate because <5 cases in reference category.

Crude 1-year survival of cancer patients from lower SES was worse compared with the highest SES for all tumour sites combined and for the major sites separately (Table 4). The age-adjusted risk of death was significantly elevated for both men (HRlow =1.40, 95% CI: 1.3–1.4) and women (HR 1.40 (1.3–1.5)). Adding comorbidity to the model reduced HR to 1.35 for men and 1.34 for women. The relative contribution of comorbidity in explaining the inequality in 1-year survival varied from 0% for lung cancer to 33% among female colorectal cancer patients.
Table 4

Crude survival, risk of death, and contribution of comorbidity to risk of death according to tumour site and SES among cancer patients diagnosed in 1997–2006

  1-year survival rate (%)
Model Aa Model Ba Relative contribution
  Low SES Inter-mediate High SES HRc (95% CI) HRc (95% CI) comorbidityb
Males
 Colorectum7278781.13 (1.0–1.3)1.10 (1.0–1.3)23%
 Lung3639411.11 (1.0–1.2)1.11 (1.0–1.2)0%
 Prostate9094951.47 (1.2–1.8)1.36 (1.1–1.7)22%
 Totald5966701.40 (1.3–1.5)1.35 (1.3–1.4)12%
       
Females
 Colorectum7478791.09 (0.9–1.3)1.06 (0.9–1.2)33%
 Lung4142461.09 (1.0–1.2)1.09 (1.0–1.2)0%
 Breast9497981.68 (1.3–2.2)1.56 (1.2–2.0)18%
 Totald7481841.40 (1.3–1.5)1.34 (1.3–1.4)15%

Model A: adjusted for age, Model B: adjusted for age and the presence of concomitant diseases (yes vs no).

((HR model A−(HR model A+comorbidity))/(1−HR model A)) × 100.

Hazard Ratio (HR) of lowest socioeconomic status (SES) group compared with highest (=reference).

All studied sites combined (oesophagus, stomach, colorectum, pancreas, lung, melanoma, breast, cervix uteri, corpus uteri, ovary, prostate, kidney, urinary bladder, non-Hodgkin's lymphoma).

Discussion

To our knowledge, this is the first large population-based study to demonstrates the impact of SES on the prevalence of concomitant diseases among cancer patients, with increased prevalence of comorbidity in lower socioeconomic strata for each type of cancer. Cancer patients with low SES had a 50% higher risk of suffering from at least one other serious disease compared with those with high SES. The prevalence of comorbidity was significantly higher with newly diagnosed cancer of lower compared with higher SES for all 14 cancer sites studied. The diseases significantly related to SES among cancer patients were cardiovascular disease, COPD, diabetes mellitus, cerebrovascular disease, tuberculosis, diseases of the central nervous system, and gastrointestinal disease. Although both the prevalence of comorbidity and the proportional distribution of SES vary significantly among tumour types, the gradient of more comorbidity from high to low SES was apparent among all tumour types. Smoking is probably responsible for the higher risk of cardiovascular disease, COPD, and cerebrovascular disease among low SES groups (Doll ; Stellman and Resnicow, 1997). This is confirmed by the higher prevalence of those diseases among patients with smoking-related tumours: cancers of the stomach, lung, bladder, and kidney (Janssen-Heijnen ; Koppert ). Diabetes was more frequent among low SES for patients with cancers of the colorectum, pancreas, lung, breast, corpus uteri or prostate, or melanoma or NHL. Diabetes has been linked to pancreas cancer (Jain ; Kalapothaki ) either as a risk factor or as the clinical manifestation of the cancer itself (Warshaw and Fernandez-del Castillo, 1992). Diabetes has also been associated with an increased risk for breast (Xue and Michels, 2007), endometrial (Parazzini ), and colorectal cancer (Polednak, 2006) probably because of a relation with obesity (Reeves ). Substantial evidence exists for the association of obesity with low SES (Sobal and Stunkard, 1989; Wardle ; McLaren, 2007). The prevalence of gastrointestinal diseases was highest for low SES patients with oesophageal, colorectal, lung, breast, prostate or kidney cancer, or NHL. Oesophageal cancer has also been associated with gastrointestinal diseases (Koppert ). A lower consumption of vegetables, fruit, and fibres, which may protect from oesophageal (Tzonou ; Terry ) and colorectal cancer (Pietinen ; Michels ; Voorrips ; Terry ; Bueno-de-Mesquita ; Flood ), has been reported among lower SES (Wallstrom ; Hulshof ; Wardle and Steptoe, 2003). We used an indicator of SES based on the postal code of a residential area. This aggregate covers a very small geographical area, and thus represents a reliable approximation of individual SES. Furthermore, routinely collected income tax data (no questionnaires or interviews) have been found to provide reliable estimates of household income. Previous studies have proven that socioeconomic differences based on neighbourhood data tend to reflect such differences well at the individual level (Bos , 2001; Smits ). Furthermore, this objective measure of SES is also applicable to older women (born before 1955), whose occupation or education does not always properly reflect their social class (Berkman and Macintyre, 1997). Previously, we found that patients with comorbidity were often treated less aggressively, if alternative treatment strategies were available. Except for patients with a tumour with poor survival, comorbidity has an independent prognostic effect (Janssen-Heijnen ). This negative impact of comorbidity on survival of cancer might have several mechanisms: the increased risk of death due to the comorbid condition itself, more contra-indications for the cancer treatment, more indications for dose reduction and a higher rate of treatment-related complications such as infections and cardiovascular events. In several of our recent studies, the adverse effects of comorbidity on survival appeared to be independent of treatment, so less aggressive treatment could not (fully) account for the observed differences in survival between patients with and without comorbidity (Post ; Lemmens ; Louwman ; van Spronsen ; Houterman ). As SES represents a combination of lifestyle, health, and risk of suboptimal treatment, cancer patients with comorbidity could also (partly) explain the poorer prognosis. Although an in-depth study remains necessary to reveal whether stage at diagnosis and treatment contributed to the SES gradient in survival, also for longer survival periods, our preliminary analyses demonstrated a clear gradient in 1-year survival rates, which could partly be attributed to comorbidity. Our study shows considerable variation in comorbidity by tumour type and a higher risk of concomitant disease among patients from lower SES. Given the aetiology of the type of tumours as well as the aetiology of the concomitant diseases that occur more frequently among patients from low SES background, a lot can probably be gained from preventive measures related to lifestyle (such as smoking and obesity). Considering survival is worse for patients of low SES, our results stress the need for reduction of socioeconomic differences in health.
  43 in total

1.  Plant foods and the risk of colorectal cancer in Europe: preliminary findings.

Authors:  H B Bueno-de-Mesquita; P Ferrari; E Riboli
Journal:  IARC Sci Publ       Date:  2002

2.  The independent prognostic value of comorbidity among men aged < 75 years with localized prostate cancer: a population-based study.

Authors:  P N Post; B E Hansen; P J Kil; M L Janssen-Heijnen; J W Coebergh
Journal:  BJU Int       Date:  2001-06       Impact factor: 5.588

3.  Fruit and vegetable consumption in relation to risk factors for cancer: a report from the Malmö Diet and Cancer Study.

Authors:  P Wallström; E Wirfält; L Janzon; I Mattisson; S Elmstâhl; U Johansson; G Berglund
Journal:  Public Health Nutr       Date:  2000-09       Impact factor: 4.022

4.  Vegetable and fruit consumption and risks of colon and rectal cancer in a prospective cohort study: The Netherlands Cohort Study on Diet and Cancer.

Authors:  L E Voorrips; R A Goldbohm; G van Poppel; F Sturmans; R J Hermus; P A van den Brandt
Journal:  Am J Epidemiol       Date:  2000-12-01       Impact factor: 4.897

5.  Fruit and vegetable consumption in the prevention of oesophageal and cardia cancers.

Authors:  P Terry; J Lagergren; H Hansen; A Wolk; O Nyrén
Journal:  Eur J Cancer Prev       Date:  2001-08       Impact factor: 2.497

6.  Fruit and vegetable intakes and the risk of colorectal cancer in the Breast Cancer Detection Demonstration Project follow-up cohort.

Authors:  Andrew Flood; Ellen M Velie; Nilanjan Chaterjee; Amy F Subar; Frances E Thompson; James V Lacey; Catherine Schairer; Rebecca Troisi; Arthur Schatzkin
Journal:  Am J Clin Nutr       Date:  2002-05       Impact factor: 7.045

7.  Fruit, vegetables, dietary fiber, and risk of colorectal cancer.

Authors:  P Terry; E Giovannucci; K B Michels; L Bergkvist; H Hansen; L Holmberg; A Wolk
Journal:  J Natl Cancer Inst       Date:  2001-04-04       Impact factor: 13.506

8.  Social inequality in incidence of and survival from cancer in a population-based study in Denmark, 1994-2003: Summary of findings.

Authors:  Susanne Oksbjerg Dalton; Joachim Schüz; Gerda Engholm; Christoffer Johansen; Susanne Krüger Kjaer; Marianne Steding-Jessen; Hans H Storm; Jørgen H Olsen
Journal:  Eur J Cancer       Date:  2008-07-30       Impact factor: 9.162

9.  Sex differences in the association of socioeconomic status with obesity.

Authors:  Jane Wardle; Jo Waller; Martin J Jarvis
Journal:  Am J Public Health       Date:  2002-08       Impact factor: 9.308

Review 10.  Lung cancer in Europe in 2000: epidemiology, prevention, and early detection.

Authors:  Jerzy E Tyczynski; Freddie Bray; D Maxwell Parkin
Journal:  Lancet Oncol       Date:  2003-01       Impact factor: 41.316

View more
  44 in total

1.  Metabolic components and recurrence in early-stage cervical cancer.

Authors:  Hee Kyung Ahn; Jin Woo Shin; Hong Yup Ahn; Chan-Yong Park; Nak Woo Lee; Jae Kwan Lee; In Cheol Hwang
Journal:  Tumour Biol       Date:  2014-11-15

2.  Cigarette smoking is associated with adverse survival among women with ovarian cancer: Results from a pooled analysis of 19 studies.

Authors:  Camilla Praestegaard; Allan Jensen; Signe M Jensen; Thor S S Nielsen; Penelope M Webb; Christina M Nagle; Anna DeFazio; Estrid Høgdall; Mary Anne Rossing; Jennifer A Doherty; Kristine G Wicklund; Marc T Goodman; Francesmary Modugno; Kirsten Moysich; Roberta B Ness; Robert Edwards; Keitaro Matsuo; Satoyo Hosono; Ellen L Goode; Stacey J Winham; Brooke L Fridley; Daniel W Cramer; Kathryn L Terry; Joellen M Schildkraut; Andrew Berchuck; Elisa V Bandera; Lisa E Paddock; Leon F Massuger; Nicolas Wentzensen; Paul Pharoah; Honglin Song; Alice Whittemore; Valerie McGuire; Weiva Sieh; Joseph Rothstein; Hoda Anton-Culver; Argyrios Ziogas; Usha Menon; Simon A Gayther; Susan J Ramus; Alexandra Gentry-Maharaj; Anna H Wu; Celeste L Pearce; Malcolm Pike; Alice W Lee; Rebecca Sutphen; Jenny Chang-Claude; Harvey A Risch; Susanne K Kjaer
Journal:  Int J Cancer       Date:  2017-01-24       Impact factor: 7.396

3.  Race, Social and Environmental Conditions, and Health Behaviors in Men.

Authors:  Roland J Thorpe; Alene Kennedy-Hendricks; Derek M Griffith; Marino A Bruce; Kisha Coa; Caryn N Bell; Jessica Young; Janice V Bowie; Thomas A LaVeist
Journal:  Fam Community Health       Date:  2015 Oct-Dec

4.  Socioeconomic inequalities in relative survival of rectal cancer most obvious in stage III.

Authors:  L I Olsson; F Granstrom
Journal:  World J Surg       Date:  2014-12       Impact factor: 3.352

5.  Gene-environment interactions on the risk of esophageal cancer among Asian populations with the G48A polymorphism in the alcohol dehydrogenase-2 gene: a meta-analysis.

Authors:  Long Zhang; Yingjiu Jiang; Qingcheng Wu; Qiang Li; Dan Chen; Ling Xu; Cheng Zhang; Min Zhang; Ling Ye
Journal:  Tumour Biol       Date:  2014-01-21

Review 6.  Racial and ethnic disparities in hematologic malignancies.

Authors:  Kedar Kirtane; Stephanie J Lee
Journal:  Blood       Date:  2017-07-19       Impact factor: 22.113

7.  Risk-reduction opportunities in breast cancer survivors: capitalizing on teachable moments.

Authors:  Krista Beth Highland; Alejandra Hurtado-de-Mendoza; Cassandra A Stanton; Chiranjeev Dash; Vanessa B Sheppard
Journal:  Support Care Cancer       Date:  2014-09-21       Impact factor: 3.603

8.  Educational differentials in cancer mortality and avoidable deaths in Lithuania, 2001-2009: a census-linked study.

Authors:  Domantas Jasilionis; Giedre Smailyte; Ieva Vincerzevskiene; Vladimir M Shkolnikov
Journal:  Int J Public Health       Date:  2015-10-01       Impact factor: 3.380

9.  Disparities and Trends in Genetic Testing and Erlotinib Treatment among Metastatic Non-Small Cell Lung Cancer Patients.

Authors:  Lauren L Palazzo; Deirdre F Sheehan; Angela C Tramontano; Chung Yin Kong
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-02-20       Impact factor: 4.254

10.  Quantifying the contributions of behavioral and biological risk factors to socioeconomic disparities in coronary heart disease incidence: the MORGEN study.

Authors:  Kiarri N Kershaw; Mariël Droomers; Whitney R Robinson; Mercedes R Carnethon; Martha L Daviglus; W M Monique Verschuren
Journal:  Eur J Epidemiol       Date:  2013-09-14       Impact factor: 8.082

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.